283
Chakravarthi Narasimhan
Abstract
Trade promotions are price incentives given by manufacturers of products and services to their intermediaries such as a dealer, distributor and retailer as part of their overall marketing strategy.
In this chapter past research on trade promotion is examined and issues relating to the rationale behind these, the potential impact on the channel partners and managerial aspects of implemen- tation are discussed. Key research issues for researchers working in this area are highlighted.
1. Introduction
In many B2C markets manufacturers distribute their products and services through a set of intermediaries. These are retailers, distributors and brokers. See Figure 13.1.
Whether there is only a retailer between the manufacturer and consumer or multiple layers of channel members might depend on the size of the retailer and other factors.
Manufacturers use multiple instruments to promote their products to their customers (retailers) and consumers (end users) to stimulate demand and grow. Promotional instru- ments directed at consumers include advertising, consumer promotions such as coupons, contests, special packages and other incentives. Incentives directed at the trade are trade promotions, category management initiatives such as assistance with planograms, mer- chandising support, demand forecasts, inventory support etc. Trade promotions are incentives given by a manufacturer of products and services to its supply chain partners, distributors/dealers/retailers, to promote its products to the ultimate end users. Trade promotion spending has been averaging around 14 percent of sales over the last 15 years or so (AC Nielsen Co., 2004). A similar report by AC Nielsen in 2004 states that 53 percent of manufacturers and retailers report ‘a measurable increase’ in trade promotion spending, while 35 percent and 36 percent of manufacturers and retailers respectively are satisfi ed with the value they get out of trade promotions. An Accenture report on
‘Capturing and sustaining value opportunities in trade promotion’ (2001) reports that while advertising, consumer promotion and trade promotion account for 23 percent of sales in 2005, trade promotion alone accounts for 13 percent of sales, quite consistent with the AC Nielsen report. Whether trade promotions are effective in delivering the stated goals for the manufacturers is debatable. The above-cited Accenture report, for example, claims that while CPG (consumer packaged goods) manufacturers spent in excess of $25 billion on trade promotion in 2005, the incremental revenue was only $2–4 billion, sug- gesting that, at the aggregate, trade promotions lost money for the manufacturers. Citing a Forrester Research report, Inforte Corp. claims in its report that in 2002 manufacturers spent $80 billion on trade promotion with an annual growth rate of 5–8 percent (Inforte
* I would like to thank Tingting He and Sudipt Roy for their assistance in assembling the Reference section. I thank Vithala Rao and an anonymous reviewer for their valuable comments and suggestions.
Corp., 2005). A recent Booz Allen Hamilton report states that ‘manufacturers are so focused in generating additional volume that the overall efficiency of their trade invest- ment is low’, and goes on to claim that manufacturers lose a third of the money spent on trade promotions (Booz Allen Hamilton, 2003). This report also states that trade promo- tion is the second-largest item in the profi t and loss account next only to COGS (cost of goods sold). While in nominal terms the money spent has been increasing, as a percentage
Manufacturer
Distributors/
brokers
• Consumer promotions
• Advertising
Consumers
Legend:
Product flows
Trade promotions & incentives Consumer promotion & incentives
Retailer
Figure 13.1 Manufacturer–consumer link in a supply chain
of sales, at least in CPG, it has been in a narrow range between 13 and 15 percent. From these industry studies reported in the popular press and research reports by various agen- cies it seems clear that trade promotion is an important marketing mix variable, CPG manufacturers predominantly use it, these promotions take different forms, and their efficiency in delivering the stated goals of the manufacturers is debatable.
In this chapter I summarize the extant academic literature on trade promotions and identify key research issues relevant to academics and practitioners. The reminder of the chapter is organized as follows. In Section 2, I provide some background on the types and forms of incentives that manufacturers provide to the trade. In Section 3, I examine analytical and empirical literature on retailer behavior relating to such practices and manufacturers’ incentives to offer trade promotions. In Section 4, I discuss issues that pertain to the evaluation of the efficacy and profi tability of trade promotions. In Section 5, I discuss literature on the role of trade promotion as part of the marketing mix. I con- clude the chapter with a discussion of key issues.
2. Types of trade incentives and objectives of trade promotions
If we defi ne trade incentives as broadly any money or allowance provided to the trade, then these incentives take many forms. Blattberg and Neslin (1990) list several different types of trade incentives for durable and non-durable products. Among the main ones are:
1. Slotting and renewable allowances These are payments made to the trade for stock- ing a manufacturer’s product, often on a per SKU (stock-keeping unit) per store basis. While stocking fee or allowance is normally associated with new products, renewable allowances are sometimes paid on existing products as well.
2. Display or feature allowance Money paid for setting up special displays of a manu- facturer’s product or advertising the product.
3. Co-op advertising allowances, where the manufacturer lets the retailer participate in a manufacturer’s advertising or pays part of the cost.
4. Off-invoice allowance Here the manufacturer sells a product, as many units as the retailer desires, at a lower price than given on a regular list price. Such a promotion may last anywhere from one to several weeks.
5. Scanback allowance Here the manufacturer reimburses the retailer an amount on every unit sold over a specifi ed period. Thus, while off-invoice is a price reduction on every unit bought, scan-back allowance is on every unit sold by the retailer over a specifi ed period.
6. Free goods Usually a case free for every n cases bought by the retailer. For all practi- cal purposes this is almost like an off-invoice promotion but forces the retailer to buy n cases before he can get the price reduction.
7. Volume discounts, based on the past year’s purchases.
These incentives are usually accompanied by certain ‘requirements’ that retailers have to meet. For example, cigarette manufacturers pay promotion money depending on facings, types of display, in-store advertising etc. (Bloom, 2001). The extent of these pro- motions varies depending on the type of retail outlet, such as supermarkets, drug stores, mass merchandisers/discounters, convenience stores and warehouse clubs, and type
of categories, such as CPG, cigarettes and drugs. Similarly, slotting allowances would require a minimum level of facings, inventory support and so on. Unfortunately there is very little systematic documentation of these and their trends over time. As stated in the Introduction, the level of these promotions has increased over time. Thus, while there are many types of trade incentives, the term ‘trade promotions’ as used in marketing refers to per unit reduction in wholesale price, and for most of the remainder of this chapter I review and consider research that focuses on this type of incentive.
2.1 Strategic objectives of trade promotions
There are several objectives of trade promotion. I list the major ones below.
1. Liquidating excess inventory When demand and supply are out of sync, a fi rm may be saddled with excess inventory in the supply chain and needs to get rid of it. Common examples are seasonal items such as snow throwers and lawn mowers, and end-of season model clearances in apparel, certain electronic items and automobiles.
2. Introducing new product Trade promotions provide a discount from a reference price to convey to consumers and the trade that the product is sold at an introductory discount. If the retailers in turn choose to pass through some or the entire discount, this could stimulate initial trial.
3. Stimulate demand If there are segments of consumers that would react differently to retail promotions, then trade promotions can be an effective tool to reach them.
4. Competitive response In response to trade promotions offered by competing manu- facturers, a fi rm may choose to offer trade promotions. Of course this begs the ques- tion as to why the other manufacturers offered trade promotions to start with.
2.2 Trade promotion as part of the overall pricing strategy
In marketing their products to the ultimate end users through a set of intermediaries (see Figure 13.1), manufacturers use the entire marketing mix to gain acceptance of their products by the trade and to penetrate the end user market. Conditional on product quality, assortment, fl avors or product line, and branding, the marketing mix used to achieve these objectives is price, advertising, and consumer and trade promotions.
Thus the role of trade promotions needs to be understood in the larger context of brand competition, supply chain power and brand equity or brand strength. There is clearly a tradeoff between using more of one type of promotion versus another or advertising or a lower price.
In the early 1990s, for example, P&G made a strategic choice to streamline their product offerings by reducing the massive amount of trade and consumer incentives and adopting an EDLP strategy for many of their products. Similarly, recent empirical evi- dence suggests that slotting allowance, a form of trade incentive offered by fi rms to gain distribution for new products, has been on the rise. If the result of a trade promotion is to stimulate demand by encouraging retailers to promote the product in turn, a natural question that must be asked and answered is ‘Why are these promotions temporary and why not set a low “regular” price rather than periodically providing discounts to the trade?’ Thus fi rms should strategically choose the level of importance and amount of money spent on trade promotion as a part of their overall mix, and not in isolation or as an afterthought. This means that the strategic objectives of trade promotion should be
understood and the allocation to trade promotion should be made in conjunction with the regular price. We revisit this issue in the fi nal section.
3. Retail response to manufacturers’ promotions
Before I offer plausible reasons why manufacturers may want to give promotions to the trade, it is instructive to examine how a retailer might respond and the documented evidence in support of this. Almost the entire academic literature considers only price-off promotions, i.e. either off-invoice or scanback promotions, and I shall therefore confi ne myself to these types of promotion.
When a manufacturer offers a price-off incentive, what would be the response of the retailer in terms of the retail price he charges? By this we mean what is the impact of a trade promotion on the retail price of the promoted product and perhaps even other products in the category? Most retailers are multiproduct retailers. A retailer also com- petes with other retailers in his trading area. If we assume that retailers want to maximize the total store profi t, then a retailer’s response to a manufacturer’s promotion would depend on a host of factors that include the brand strength of the promoted product, its ability to attract consumers, the available substitutes and complements and the margins on these, the potential action of other retailers etc. From an analytical point of view it is worthwhile to characterize the role of these drivers and reconcile these with the empirical facts. We start with the empirical papers.
3.1 Empirical facts and documented evidence
The empirical literature on retail response has addressed two issues. What is the rate of retail pass-through and what are some factors that affect this? By pass-through we mean the percentage of money that is received from a manufacturer that is passed through to the ultimate consumers, or, more specifi cally, the change in the retail price due to a change in the wholesale price. Thus 100 percent pass-through means that every penny that is received via a wholesale price reduction is refl ected as a penny reduction in the retail price.
Chevalier and Curhan (1976) examined over 990 trade promotions received by a single grocery chain and found that the chain supported only about one-third of the products with any kind of promotional support in the form of a price cut, display or feature adver- tising. Over 45 percent of the products for which the chain got trade promotions did not receive any retail support. But, conditional on promoting through a price reduction, the average retail pass-through rate was 126 percent. Moreover, the authors found that the sales movement of the brand had a signifi cant impact on the retail support while package size, rank of a product in its category or the amount of money received had no predictable impact. Somewhat contrary to this, Walters (1989), using data from two grocery chains, found that the size of the incentive has a positive effect on the level of retail support. In addition he found that sales volume (consistent with Chevalier and Curhan), compliance requirements (such as manufacturer-paid feature or display support) and price elasticity of the brand affect positively the level of retail support. Armstrong (1991) also documents that across many categories pass-through rates vary, and can be greater than 100 percent.
More recently Besanko et al. (2005) examined own-brand and cross-brand retail pass- through using data from a supermarket chain in 11 categories and 78 products. They estimate a reduced-form model of the following form:
P{i} 5f (c{i}, c{2i}, d) (13.1) where P{i} is the retail price of brand i, c{i} is the wholesale price of brand i, c{2i} is a vector of wholesale prices of all other brands in the category and d is a vector of exog- enous shift variables. They estimate the above model using liner, log linear and a fl exible polynomial specifi cation. The estimates of interest are the marginal change in P{i} with respect to a small change in c{i} and c{2i}, that is own- and cross-brand pass-through.
They estimate (13.1) for each product, using the three specifi cations mentioned, by pooling data across different price zones of the chain and including shift variables to control for interzone heterogeneity. They report that nearly 70 percent of the estimates of pass-through are signifi cant and positive. This pass-through rate varies signifi cantly across categories with beer and detergent getting larger pass-through than categories such as toothpaste and paper towel. The range is quite large, with average pass-through rate of 22 percent in toothpaste to over 550 percent in beer. The pass-through rate on own brand is on average more than 60 percent in most of the categories they examined. They fi nd the cross-brand pass-through to be positive and negative. They fi nd that market share, and a brand’s importance or contribution to the category profi t positively infl uence pass-through. Moreover, a large brand’s promotion is less likely to generate cross-brand pass-through on smaller brands than the other way around.
The data used by Besanko et al. come from a chain where the recorded wholesale price is not the actual wholesale price but rather is an ‘average acquisition cost’ (see Peltzman, 2000) that is based on a weighted average of past prices and past inventory.
Thus it is not the strategic choice variable of the manufacturer. This leads to a potential bias towards overstating the pass-through effect and the size of the bias is unknown.
Meza and Sudhir (2006) claim that in the presence of forward buying by a retailer, using this acquisition cost measure as a proxy for true wholesale price leads to less of a bias than not using the inventory data at all. McAlister (2005) takes issue with Besanko et al.’s methodology and conclusions. She argues that a typical retailer carrying around 30 000 SKUS will be unable to optimize as the model claims; manufacturers would rationally withhold trade promotion support if they know that their brands’ retail prices can fl uctuate depending on their competitors’ promotions; variability of promotional deals masks the true wholesale prices; measurement errors exist in accounting for pro- motions etc. Conducting a more detailed analysis of the detergent data Besanko et al.
used, McAlister offers further support for the view that the signifi cance of cross-brand promotions is overstated.
Meza and Sudhir (2006) criticize earlier empirical studies for the methodology used to uncover the pass-through rate. Since a typical grocery product category is subjected to seasonal demand shocks, retail prices could be adjusting to these shocks independent of any wholesale price fl uctuations and therefore this needs to be accounted for in determin- ing pass-through rates. Starting with a random utility model at the individual level and aggregating to the store-level demand for a brand, they estimate store-level market share equations using the same database as Besanko et al. However, they estimate using only two categories: tuna, which was used by Besanko et al., and beer, which was not used by Besanko et al. By estimating a demand model with data from 94 stores over 400 weeks they infer the pass-through rates and show that loss leaders receive a higher pass-through than other products, and that this rate is lower during periods of high demand.
To summarize, the empirical literature documents the following:
Not all trade promotions are refl ected in retail promotions or pass-through.
●
There is considerable variation in this pass-through across brands and across
●
categories.
The pass-through rates can be more than 100 percent and often, in some categories,
●
substantially more.
A brand’s market share and sales volume a
● ffect positively the rate of pass-
through.
There is some evidence that the cross-brand pass-through and a smaller brands
●
trade promotion might lead to pass-through on a larger brand. But more analysis is needed to establish this more convincingly. Similarly, certain categories, due to their importance in attracting store traffic, could potentially receive a higher pass- through.
Thus, while we have evidence on the variability of pass-through, a more systematic analysis of the behavior of wholesale prices and retail prices needs to be conducted to make accurate inferences about the impact of wholesale prices on retail prices. This means that we need econometric models grounded in theory that simultaneously account for the behavior of wholesale and retail prices so that we can make inferences about the impact of the former on the latter. Notwithstanding my admonition, how can these tenta- tive ‘facts’ be reconciled with optimal behavior of market players? To assess this, we turn to the analytical literature.
3.2 Analytical models of retail response to trade promotions
Tyagi (1999) characterized the optimal response of a single-product monopoly retailer faced with a trade promotion, i.e. reduction in the wholesale price. The retailer is a Stackelberg follower in pricing, and takes the wholesale price as given and sets the retail price. He showed that if the retail demand function is concave or quasi concave, the pass-through rate is <100 percent and if convex, such as a constant elasticity demand function, then the pass-through rate is greater than 100 percent. His paper thus offers support for >100 percent pass-through based purely on the shape of the demand func- tion. Kumar et al. (2001), in their attempt to explain the empirical facts, consider a single manufacturer–retailer dyad selling a single product. The elements of their model are as follows:
There are two segments of consumers, low valuation and high valuation, that
●
derive net utility of v 2 p and d*v 2 p respectively, where v is the intrinsic utility for the single product in the market, p is the price and d > 1.
Consumers know the frequency (
● a) with which manufacturers offer trade promo- tions, and on observing the retail price at the focal retailer make inference about whether the retailer is being opportunistic (not passing on the trade promotion) or whether the wholesale price is really high and consequently the retail price is at its regular level.
Based on this, consumers decide to buy from this retailer or choose an outside
●
option, which is to buy from another retailer.
The manufacturer can use advertising to mitigate the retailer’s opportunism
●
by choosing to inform a fraction (w) of the market about the trade promotion offer.
The game sequence is as follows. The manufacturer selects
● w, the retailer selects the
likelihood he would offer a consumer promotion. Consumers observe w and the retail price and decide whether or not to buy from this retailer.
Kumar et al. show that, in this world, the retailer does not always pass through and is less likely to pass through the greater the level of discount (inconsistent with Walters, 1989), lower the frequency of trade promotions, and lower the manufacturer support through advertising of the promotions (consistent with Walters, 1989).
Lal and Villas-Boas (1998) consider more complex consumer heterogeneity in the presence of retail and manufacturer competition, with each manufacturer selling a single product. There are two manufacturers selling one product each through two retailers and consumers can be in one of nine segments (size): a most price-sensitive segment (S) that buys the cheapest product in the market, two retailer-loyal segments (R) that buy from a single retailer the lowest-priced product, two manufacturer-loyal segments (M) that buy from the cheapest retailer, and four retailer–manufacturer-loyal (that is they are loyal to one retailer and one brand) segments (I). All consumers buy one unit of the product as long as the price is less than the common reservation value r. The game is set as follows:
Manufacturers set wholesale prices simultaneously to maximize profi ts.
●
Retailers take the wholesale prices as given and set retail prices simultaneously to
●
maximize their profi ts.
Consumers decide on the store and brand to buy.
●
When there is no retailer loyalty (R 5 I 5 0), there is no retailer power and retail prices equal wholesale prices, which follows the equilibrium described in Narasimhan (1988).
Similarly, when there is no manufacturer loyalty (M 5 I 5 0), the manufacturers have no market power, wholesale prices equal marginal cost and now the retail prices track Narasimhan’s model. When the market consists of no manufacturer switchers, i.e. R 5 S 5 0, all prices are equal to r. If there are no retail switchers, i.e. M 5 S 5 0, retail prices equal r and manufacturers randomize as in Narasimhan’s model.
In the more general cases Lal and Villas-Boas show that the retail equilibrium can be quite complex depending on the relative magnitudes of the segments, and in some cases, it is possible for the retailer not to promote a brand when that brand’s wholesale price is lowered, i.e. under trade promotion. Moreover, in some cases the brand that has the highest wholesale price can have the lowest retail price. An important contribution of this paper is to show when results from prior work such as Narasimhan (1988) will continue to hold and when the equilibrium will be qualitatively different.
Moorthy (2005) extends this literature by considering multiproduct retailers and retail competition. Consider for example two retailers carrying two brands, each with one brand common between the two and the other an exclusive brand that can be interpreted as a private label. Unlike in much of the literature, the demand functions are assumed continuous functions of all prices. In addition to wholesale price changes, the author
considers variety of cost shocks that could lead to a change in retail price. The profi t function for retailer i can be written as
IIi(P) 5 (pi12w12ci12ci2c) Di1 (P) 1 (pi22ci22ci2c) Di2 (P) (13.2) where P is the vector of all prices
w1 is the wholesale price of the brand that is common among retailers ci1 and ci2 are retailer i’s brand-specifi c marginal costs
ci is retailer i’s non-brand-specifi c marginal cost such as labor cost c is a non-brand, non-retailer-specifi c cost such as excise cost
Di1 and Di2 are the demand functions for product 1 and 2 respectively at retailer i.
Moorthy examines how, if the retailer maximizes category profi ts, retail prices will change with respect to wholesale price and the different marginal costs. He shows that the response due to a trade promotion is always positive, leading to a retail promotion.
This pass-through would be greater with retail competition and the adoption of category management by the retailers. He also shows that cross-brand effects are ambiguous, i.e.
can be both positive and negative, a conclusion supported by Besanko et al.
To summarize, analytical models explain how optimizing retailers’ behavior can lead to (i) pass-through of trade promotion, (ii) the pass-through can be greater than 100 percent depending on the shape of the demand function, (iii) in some instances the retailer may not pass through at all, and (iv) cross-brand pass-through can arise but its direction can be positive or negative.
3.3 Manufacturers’ incentives to offer trade promotions
At the heart of trade promotions is the question: why do manufacturers offer temporary reduction in wholesale prices? Notice that there are two questions here: (i) why is the incen- tive tied to the wholesale price as opposed to lump sum payment such as a display support or feature support, and (ii) why are these promotions temporary? The null hypothesis on the second question is: why not offer a permanent reduction in wholesale price? Clearly, if there are demand (seasonality, mismatch between forecast and realization of demand etc.) shocks or supply shocks (crop prices, labor costs) we should observe a temporary fl uctua- tion on wholesale prices. But most trade promotions cannot be dismissed as arising out of these random shocks. There must be consumer, supply chain and competitive factors that lead to such promotions. This second question takes on added importance when we factor in the direct and indirect costs of trade promotion (see Buzzell et al., 1990). One of these costs is the opportunity cost or foregone profi t if retailers forward buy on trade promotions. If retailers buy more than what they require to meet the compliance require- ments and use the additional quantity to sell the product at its normal regular price, this represents a loss or cost of that trade promotion. We examine the answers provided by analytical models of consumers, intermediaries and manufacturers.
Jeuland and Narasimhan (1985) offered a model of two parties – a monopoly fi rm and consumers – to explain the occurrence of promotions. There are two segments of consum- ers who differ in their preferences and inventory costs. The demand for a product at the segment level is given by
Qi5 ai2 b*P (13.3) where Qi is the demand for segment i and P is the retail price, ai is the segment specifi c parameter and b is the price sensitivity parameter.
The authors assume that the segment with higher a has a higher holding cost for inventorying this product, only buys for current consumption and does not forward-buy.
The consumers with lower a, when faced with a retail promotion, respond by increasing their consumption and forward buying the product when it is on sale. They show that the optimal strategy for the monopolist is to conduct periodic sales and solve for the fre- quency and depth of promotion. The contribution of this paper is to show that consumer heterogeneity in inventory costs and demand elasticity, and correlation between these, can drive periodic promotion by a manufacturer. While they didn’t identify the consum- ers as retailers, they could apply their model to trade promotions as well. As long as there are enough customers able to expand their demand and forward-buy, it is optimal for the fi rm to offer trade promotions. Lal (1990) offers a model with two competing manufactur- ers marketing one brand each through a retailer who offers a store brand. He shows that in an infi nitely repeated game the manufacturers take turns to offer a trade deal to the retailer. Thus in a non-cooperative game the manufacturers collude to limit the encroach- ment by the store brand into their franchises. Lal et al. (1996) consider a model of two competing manufacturers selling one product each through a common retailer. The manufacturer incurs a selling cost of promotion and the retailer, if he accepts the promo- tion, incurs a fi xed cost. The retailer can buy the product either at the regular price or at the promoted price and can forward-buy products for future use. The demand model has features similar to models without a retailer (see Narasimhan, 1988). As in earlier models, manufacturers use a randomized strategy in offering discounts to induce the retailer to inventory their products. An important contribution of this paper is to show that even when the retailer forward-buys, manufacturers fi nd it profi table to offer a trade deal. The reason is that holding inventory leads to less intense price competition since smaller deals are less attractive to the retailer when he has inventory and larger deals become unprofi t- able to the manufacturers. So the manufacturers compete over a narrower range of trade deals, which means that the probability of beating your opponent (i.e. the retailer will accept the deal) is lower and therefore the manufacturers are less aggressive.
A paper that models manufacturer promotion not as a wholesale price reduction but as a lump sum transfer is by Kim and Staelin (1999), who consider a model of two manu- facturers selling one product each and two retailers who sell two products each. Trade promotion is captured through a lump sum allowance that a manufacturer provides a retailer. Each retailer selects the retail prices and a common pass-through rate for the two brands. The ‘pass-through rate’ is the proportion of this allowance spent on merchandis- ing activity that affects demand positively. Retail demand for brand i at the retailer is given by the following:
Demand for brand 1 at store 1 5 f (prices of all brands at store 1, pass-through rate at store 1*difference in the promotional allowance of brand 1 in store 1, difference in promotional allow- ances across stores, pass-through rate at store1*promotional allowance at store1)
Thus the demand function captures the effect of prices, own- and cross-brand pass- through, store switching and category expansion. The game proceeds as follows. Each
manufacturer simultaneously chooses wholesale price and promotional allowance for his brand, anticipating the actions of the retailers. In the second stage, retailers simultane- ously choose retail prices and pass-through rates. Two broad conclusions emerge from this paper. First, it offers analytical support to the evidence and argument made earlier by Messinger and Narasimhan (1995) that even when manufacturers provide greater con- cessions to the retailers, because of retail competition these concessions are passed along aggressively by the retailers. Second, the authors show that even though retailers pass through less than they receive, manufacturers provide the side payments to the retailers.
A different rationale for the existence of trade promotions and allowances is provided by the research stream that examines the channel relationship when the retailer not only dis- tributes manufacturers’ products but also markets a store brand. Narasimhan and Wilcox (1998) consider a manufacturer–retailer channel where the retailer is able to procure a private label in a competitive market. There are two segments of consumers, one loyal to the national brand and another that is composed of national brand–private label switchers. All consumers buy one unit of either the national brand or the private label as long as the price of that product is less than $r, the reservation price. A randomly chosen consumer in the switching has a preference for the national brand but will buy the private label if the retail price of the private label is $l less than the national brand. They assume that l is distributed U (0, L). The manufacturer sets his wholesale price anticipating retailer’s pricing behavior in relation not only to the national brand but also to the private label. They compute the equilibrium prices with and without private labels. They show that the retail margin on the national brand is positively related to the size of the switching segment and is negatively related to the heterogeneity of the switching segment. The fi rst result is obvious. The second result arises due to the fact that as the heterogeneity in the switching segment increases, it is more costly for the retailer to attract the same proportion of switchers away from the national brand, which leads to lower concession from the manufacturer. The authors thus show that not only does a private label have a direct effect in terms of attracting more cus- tomers in the market; it also has a strategic effect of eliciting better wholesale price conces- sions from the manufacturer. They offer empirical support to their predictions.
To summarize, we have the following predictions from the analytical models:
Retailers in general will pass through manufacturers’ incentives. Greater than 100
●
percent pass-through is predicated upon the shape of the demand curve.
Ignoring menu costs and adjustment costs of changing prices, cross-brand pass-
●
through is likely to occur.
Even if retailers forward-buy, in a competitive world we should see trade
●
promotions.
Retail competition forces retailers to pass through more than they would normally
●
have passed through based on demand and cost curves.
Trade promotions or concessions from manufacturers can arise when retailers
●
market store brands or private labels.
4. Profi tability and efficacy of trade promotions
In this section we discuss two key managerial issues: (i) how should one evaluate the prof- itability of trade promotions and (ii) how can one make trade promotions more effective in achieving stated objectives?
4.1 Evaluating the profi tability of trade promotions
At fi rst glance this seems a very simple task. Compare the profi ts with and without promotion and if the latter are greater than the former, declare victory because the pro- motion is profi table. But closer examination reveals that it is not simple: evaluation of promotion is fraught with many measurement and data problems. To understand the difficulties, let us think about what happens when a promotion occurs by focusing on off-invoice promotion. If retailers anticipate that such promotions are temporary, they are likely to be strategic and engage in forward-buying. Likewise there is a large body evidence that consumers, when faced with retail promotions, forward-buy; more recent evidence (see, e.g., Van Heerde et al., 2003; Chan et al., 2008) seems to suggest that such stockpiling behavior accounts for a major portion of the sales spike. The amount that is forward bought is potentially an opportunity loss since these units could have been sold at the regular price at some point later in time. Of course not all of it is a loss since there is no guarantee that the retailer would have bought the same amount in future. Moreover, wholesale demand and retail demand of a product are subject to random shocks and competitive actions. Given all this, determining incremental sales due to a promotion is a complicated task. If consumers and retailers act strategically, examining shipments data in a ‘before versus after’ promotion analysis will be misleading. Next is the ques- tion of identifying direct and indirect costs of promotion. What are the direct costs of running a trade promotion? What about the indirect or opportunity costs of accumulat- ing higher inventory in preparation for a promotion etc? Thus, even if one can estimate the incremental sales, identifying the direct and indirect costs to evaluate profi tability of promotions is daunting. Two papers tried to tackle the profi tability of promotion using sales and shipment data.
Blattberg and Levin (1987) use a three-equation model and an accounting identity to predict shipments and consumer sales as below:
Shipments {t}5f1 ( inventory {t21}, trade promotions, other factors ) Retail promotions {t} 5f2 ( trade promotions {t}, trade promotions {t21},
inventories {t21} )
Consumer sales {t}5g ( trade promotions {t}, retail promotions {t21}, other factors {t}, other factors {t21} )
Inventories {t} 5h ( inventories {t21}, shipments {t}, consumer sales {t} ) They estimate the model using data from ten products and three markets. Using the esti- mates, one can simulate what will happen when a trade promotion is offered to shipments and retail sales. This model, by being theoretically sound in that it relies on a process model of the fl ow of goods and money in the system, gives confi dence as to face valid- ity. While this is a good beginning, note that they were not able to estimate separately, due to data problems, the second equation above to uncover the factors that drive retail promotions. Moreover, there was no attempt to explicitly control for or model within- category competitive effects or interstore competition. Finally, the consumer sales model can be enriched to include drivers under the control of the retailers such as feature and display support etc.
Abrahim and Lodish (1987) develop an expert system to evaluate the impact of promo- tion. Their focus is on identifying baseline sales, those that would result in the absence of promotional effects. They defi ne sales at time t as
S(t) 5T(t) * SI(t) * X(t) (b(t) 1p(t) 1e(t) )
where T, SI, X are trend, seasonal and ‘exception’ indices, b, p are the base-level sales and promotional bump after removing trend, seasonality and ‘exceptions’, and fi nally e is an error term. Through data analysis and judgment the baseline sales is estimated and, using that, the incremental sales and profi tability of any promotion can be estimated.
Unlike the Blattberg and Levin model, this model is purely data driven and the statisti- cal property of the baseline sales is not known. Further, the procedure for identifying exceptions seems not to follow from any structure but rather depend on the analyst’s judgment. For example, the authors report that category-level and competitive effects are captured by the exception index but it is not made clear how; nor is the robustness of this index measured.
To summarize, there have been some attempts to model the profi tability of trade pro- motions. Largely due to the type of data available and the cost of conducting this exercise, we have not seen more of this type of research but it remains an important area.
4.2 Drivers of effective trade promotions
What are the drivers that improve the effectiveness of trade promotions? How can we use these drivers to optimize the timing and characteristics of promotional offers? To answer the fi rst question, we should develop metrics for effectiveness. Is it just profi tability, or are there other measures that we should examine? Hardy (1986) explored this issue through a survey of managers from a sample of 27 Canadian packaged good companies on 103 trade promotions. Each manager was asked to complete the survey instrument for one successful and one unsuccessful promotion. Using these data, Hardy examines through a multiple regression model the drivers for the following four dependent variables:
short-term volume, long-term market share, build-up of trade inventories and increased consumer trial. He found that trade support had a predictable impact on all the four metrics. The level of incentives affected positively the short- and long-term share goals while competitive promotion affected negatively the build-up of inventories, with the trade, of the focal brand. These results are intuitive. Blattberg and Neslin (1990), based on a study by Curhan and Kopp (1986), identify the following four factors as infl uencers on the level of support the retailers would provide:
1. Economic structure of promotions such as amount of discount, terms, requirements and restrictions.
2. Item importance, including volume, category size and competitive retail activity.
3. Manufacturer’s reputation.
4. Promotional elasticity.
Murry and Heide (1998) consider the issue of retailer participation and compliance with manufacturer-initiated promotions such as POP programs. They theorize that both interpersonal relationship and incentives matter in retailers’ decisions. They designed a
conjoint study that included four factors (two levels each) to capture both organizational and incentive drivers. The study was administered using a full factorial design to liquor and grocery store managers. They found that incentive factors are more important in the decisions of the retailers, and that strength of interpersonal relationship does not dimin- ish this importance.
Which type of trade promotions would be best and what are the drivers? This is some- what of an underresearched area. Given the structure of these promotional incentives, it is not surprising that manufacturers tend to favor performance-based promotions such as scan-backs while the retailers favor straight off-invoice promotions. Drèze and Bell (2003) show analytically that if the terms of the deals are identical, the above result is valid, but a manufacturer can redesign the scan-back promotion to leave the retailer no worse off while improving his profi tability. This is because under scan-back there is no excess ordering and retail price is lowered, resulting in higher retail sales. In their model there is no manufacturer or retail competition, so it is not clear how these added institu- tional details would change the result.
5. Trade promotion as part of the marketing mix
As any marketing student knows, fi rms have multiple instruments to stimulate demand and to respond to competitive and channel initiatives. So where does trade promotion fi t as part of the overall marketing strategy? How should managers address the problem of budget allocation? I explore these issues in this section.
Narasimhan (1989) explores the factors that are perceived to be important in deciding on consumer and trade promotions. He conducted a survey of brand managers to assess this. He identifi ed three factors that drive the importance attached to trade promotions.
These are goal oriented (achieving sales targets, introducing new products, motivating sales force), defensive (maintaining shelf space, meeting competition), and penetration (increasing usage rate and getting more retailer push). The factors for consumer promo- tion were similar except that there were two goal factors, one short and one long term.
He found that the managers’ beliefs about the importance of these factors were corre- lated with category and brand variables such as category, volume, growth rate, shelf life, purchase frequency, market share, rank etc. Finally, he fi nds that the decision to allocate money between trade and consumer promotions is based not only on category and brand variables but also on the perceived importance of the factors.
Neslin et al. (1995) consider a market consisting of a single manufacturer–retailer dyad and consumers. The manufacturer can advertise the product to consumers and trade-promote to its retailers. Advertising affects retail sales through the pull effect and retail promotion also affects retail sales. The manufacturer is assumed to maximize its net profi t over a year by deciding on the optimal allocation between advertising and trade promotions. Unlike the standard analytical models, they do not use a game-theoretic set-up. The amount to be ordered by the retailers, the intensity of promotion at retail level etc., do not come from maximizing behavior by the retailer but rather are written down as exogenous decisions. A demand equation describes the total sales at the retail outlet. They use numerical optimization methods to arrive at an optimal policy for the manufacturer. In the base case, for example, they show that periodic trade promotions and constant advertising expenditures except in the period before a trade promotion is an optimal strategy. While this kind of exercise incorporates a level of richness that is
not found in standard analytical models, the non-strategic behavior of retailers and con- sumers is a limitation of such an exercise.
Gomez et al. (2007) evaluate the drivers behind the allocation of the trade promotion budget and its components. They hypothesize that the amount of money allocated to trade promotion increases is positively (negatively) correlated with the size of retailer and the brand power of retailer (size of manufacturer, brand strength) while the effect of private label penetration is ambiguous. Similarly, allocation of money between off- invoice and performance-based scan-backs is also driven by these factors. Using survey data from 36 supermarkets in the USA, they test their hypotheses and fi nd support. It is interesting and somewhat intuitive that they fi nd that, with greater retailer size, position- ing and power through private label, retailers are able to elicit better concessions from the manufacturer through off-invoice promotions, a point made earlier by Narasimhan and Wilcox (1998).
Gerstner and Hess (1991, 1995) consider the dual role of trade promotions and con- sumer promotions through coupons or rebates. They consider a manufacturer–retailer dyad with no competition at either level. Consumers are of two types, H and L. The H type has a higher reservation price than the L type. All consumers desire at most one unit of the product as long as the price is less than their reservation price. The manufacturer distrib- utes the product through a retailer and decides on the wholesale price fi rst and, conditional on this, the retailer decides his retail price. As long as the L-type segment size is below a critical level, the manufacturer’s optimal strategy is to cater only to the H type. But as the L type grows it is optimal for the manufacturer and for the channel as a whole to sell to both types. But in the standard Stackleberg leader–follower game, if the manufacturer lowers the wholesale price, the retailer has every incentive not to pass along the lowered price to attract the L type due to the standard double marginalization problem. Gerstner and Hess show how the use of pull promotions through rebate or coupon can coordinate the channel. They go on to discuss the effect of coupons and what happens if perfect tar- geting of low-value consumers is not possible. This paper doesn’t capture the essence of trade promotions, which are temporary reductions in wholesale price. These papers offer insights into when a wholesale price reduction is necessary and how other marketing mix variables play a role in enhancing the effectiveness of such a policy. These papers make two interesting points. Consumer promotions in conjunction with trade promotion can coordinate the channel. Pull promotions, in addition to any discriminatory or segmenta- tion effect among end users, can serve an added role in the presence of an intermediary.
Agrawal (1996) considers the effect of brand loyalty on advertising and trade promo- tion. He constructs a theoretical model that captures two competing manufacturers dis- tributing one brand each and a common retailer that distributes both brands. Consumers desire at most one unit of either product as long as the retail price is less than $r. There are two segments of consumers each loyal to one of the two brands, but each will switch to the other brand if the price of the other brand is lower than a threshold relative to its favorite brand. The retail demand for brand i (i 5 1, 2; j 5 3 2 i) can be written as
Di (pi, pj) 5
u
M1i ifif pi2plii #, ppjj#2plji1lj0 if pj, pi2li
(13.4)
where pi and pj are retail prices, and li and lj represent the threshold the competing brand has to overcome. A fi rm’s own advertising expenditure raises, at a diminishing rate, the threshold the other fi rm has to overcome but competitive advertising lowers this threshold. So fi rm i’s advertising raises li while fi rm j’s advertising lowers li and vice versa. The author assumes that the thresholds for two brands are sufficiently different so that the brand with a larger l is called the stronger brand and the other the weaker brand. The game proceeds in four stages. In stage one, the two manufacturers simulta- neously decide on their respective advertising levels. In stage two they simultaneously set wholesale prices, in stage three the retailer sets the retail prices for the two brands and in stage four consumers observe all the prices and make their choices. He fi nds that the retailer, similar to Narasimhan’s results, promotes the stronger brand more frequently than the weaker brand. Turning to the manufacturer, he fi nds that there are several equilibria, depending on the marginal cost of advertising, where the stronger brand does not advertise but the weaker brand advertises and the promotional strategy is one of the following:
(a) Neither manufacturer promotes.
(b) Both promote and the weaker brand spends less.
(c) Both promote and the weaker brand spends more.
On pass-through of trade promotions the author fi nds that the stronger brand enjoys greater pass-through in terms of frequency but not on the size of the discount. Some of these results, especially on the pass-through, seem to be inconsistent with the empirical evidence cited earlier. Using scanner panel data, he examines some of the predictions from his model. To test these predictions he fi rst estimates the size and strength of loyalty for each of 54 brands in seven different categories. Using linear regression he estimates the following three modes at the brand level:
Advertising expenditure5 a01 a13loyalty1 a23size 1category dummies1 e1
Average retail discount5 b01 b13loyalty1 b23advertising expenditure 1category dummies1 e2
Frequency of retail promotions5 g01 g13 loyalty1 g2
3advertising expenditure1category dummies1 e3 Consistent with his theoretical predictions, he fi nds that high loyalty leads to lower adver- tising expenditures, lower retail discount and greater frequency of retail promotions, and loyal segment size is positively related to the manufacturer’s advertising expenditure. The contribution of this paper is in considering trade promotions as part of the overall mix in conjunction with advertising and promotions at both the wholesale and retail level.
6. Discussion
In this chapter I discuss several research streams examining the role of trade promo- tions, the incentives of trading partners in offering and accepting these, the drivers of the
efficacy of trade promotions, evaluating the profi tability of trade promotions and how trade promotions may interact with other marketing variables.
Manufacturers, especially CPG manufacturers, have been allocating a greater share of the promotional budget to trade promotions over time. We are also seeing a shift in the allocation among the types of promotions, partly driven by improvements in IT that have lead to better data capture, analysis and monitoring.
Existing research has evolved along the following streams:
Documenting retailer acceptance and pass-through rates.
●
Empirically identifying the drivers of retailer acceptance.
●
Analytical models exploring the rationale behind trade promotions in monopoly
●
and competitive contexts.
Analytical models characterizing the impact of promotions on retailers and their
●
propensity to accept these.
Models evaluating profi tability.
●
Understanding the drivers to improve the e
● fficacy and impact of trade promotion.
Role of trade promotion as part of the marketing mix.
●
Several conclusions emerge from the extant literature:
Retailers are selective in passing the money they receive from the manufacturers
●
to the consumers. Surprisingly, several instances have been documented where the retailers pass through more than they receive.
A brand’s strength and its ability to pull sales or increase store tra
● ffic (Lal and
Narasimhan, 1996), item importance, size and structure of incentives are key pre- dictors of retailer compliance.
Retail competition increases the pass-through rate.
●
Trade promotions can arise even if retailers forward-buy.
●
The presence of store brands or private labels acts as an important driver for
●
the manufacturers to offer concessions to trade, often in the form of trade promotions.
Cross-brand pass-through can occur, although the empirical evidence seems to be
●
somewhat scant or mixed.
Based on this, I expect future research to continue to build on this important topic along the following lines:
A broader assessment of the empirical regularities across many categories and
●
markets such as in international markets.
Exploring in greater depth the e
● fficacy and profi tability of trade promotions by
explicitly modeling retailer characteristics such as size, market share, reputation etc. in the empirical models.
Extending and checking for robustness of the fi ndings in non-grocery markets such
●
as apparel, electronic goods, toys etc. Some studies have looked at trade promo- tions in durable goods (Bruce et al., 2005) and dealer promotions in automobiles (Busse et al., 2006). More work along these dimensions would help us to understand
and establish robust drivers for the incidence, acceptance and pass-through of these trade promotions.
Examining analytically and empirically the promotion incentives, acceptance and
●
performance when there are multiple channels such as brick-and-mortar and online channels.
Examining the strategic role of trade promotions as part of the overall pricing strat-
●
egy. How exactly do or should fi rms design trade incentives and an overall pricing strategy including a regular list price?
References
Abrahim, M. and L. Lodish (1987), ‘PROMOTOR: an automated promotion evaluation system’, Marketing Science, 6, 101–23.
AC Nielson Co. (2004), ‘Summary: 2003 trade promotion practices’, Consumer Insight, Summer, available at:
http://www2.acnielsen.com/pubs/documents/2004_q3_ci_tpp.pdf.
Agrawal, D. (1996), ‘Effect of brand loyalty on advertising and trade promotions: a game theoretic analysis and empirical evidence’, Marketing Science, 15 (1), 86–106.
Armstrong, M.K.S. (1991), ‘Retail response to trade promotion: an incremental analysis of forward buying and retail promotion’, Doctoral Dissertation, UT Dallas.
Besanko, D., J.-P. Dubé and S. Gupta (2005), ‘Own-brand and cross-brand retail pass-through’, Marketing Science, 24 (1), 123–37.
Blattberg, R.C. and A. Levin (1987), ‘Modeling the effectiveness and profi tability of trade promotions’, Marketing Science, 6, 124–46.
Blattberg, R.C. and S.A. Neslin (1990), Sales Promotion: Concepts, Methods, and Strategies, Englewood Cliffs, NJ: Prentice Hall.
Bloom, P.N. (2001), ‘Role of slotting fees and trade promotions in shaping how tobacco is marketed in retail stores’, TC online, 10, 340–44.
Booz Allen Hamilton (2003), ‘Boosting the bottom line through improved trade promotion effectiveness’, Report, McLean, VA: Booz Allen Hamilton.
Bruce, N., P. Desai and R. Staelin (2005), ‘The better they are, the more they give’, Journal of Marketing Research, February, 54–66.
Busse, M., J. Silva-Risso and F. Zettelmeyer (2006), ‘$1,000 cash back: the pass through of auto manufacturer promotions’, American Economic Review, September, 1253–70.
Buzzell, R.D., J.A. Quelch and W.J. Salmon (1990), ‘The costly bargain of trade promotions’, Harvard Business Review, March–April, 2–9.
Chan, T., C. Narasimhan and Q. Zhang (2008), ‘Decomposing purchase elasticity with a dynamic structural model of fl exible consumption’, Journal of Marketing Research, 45 (4), August, 487–98.
Chevalier, M. and R.C. Curhan (1976), ‘Retail promotions as a function of trade promotions: a descriptive analysis’, Sloan Management Review, Fall, 19–32.
Curhan, R.C. and R.J. Kopp (1986), ‘Factors infl uencing grocery retailers’ support of trade promotions’, Report No. 86-104, Marketing Science Institute.
Drèze, X. and D.R. Bell (2003), ‘Creating win–win trade promotions: theory and empirical analysis of scan- back trade deals’, Marketing Science, 22 (1), 16–39.
Gerstner, E. and J.D. Hess (1991), ‘A theory of channel price promotions’, The American Economic Review, 81 (4), 872–86.
Gerstner, E. and J.D. Hess (1995), ‘Pull promotions and channel coordination’, Marketing Science, 14 (1), 43–60.
Gomez, M.I., V.R. Rao and E.W. McLaughlin (2007), ‘Empirical analysis of budget allocation of trade promo- tions in the US supermarket industry’, Journal of Marketing Research, 44 (3), 410–24.
Hardy, K.G. (1986), ‘Key success factors for manufacturers’ sales promotions in package goods’, Journal of Marketing, 50 (3), 13–23.
Inforte Corp. (2005), ‘Point of view: trade promotion effectiveness’, Report, Chicago: Inforte Corp.
Jeuland, A.P. and C. Narasimhan (1985), ‘Dealing – temporary price cuts – by sellers as a buying discrimination mechanism’, Journal of Business, 58 (3) 295–308.
Kim, S.Y. and R. Staelin (1999), ‘Manufacturer allowances and retailer pass-through rates in a competitive environment’, Marketing Science, 18 (1), 59–76.
Kumar, N., S. Rajiv and A. Jeuland (2001), ‘Effectiveness of trade promotions: analyzing the determinants of retail pass through’, Marketing Science, 20 (4), 382–404.
Lal, R. (1990), ‘Manufacturer trade deals and retail price promotions’, Journal of Marketing Research, 27 (4), 428–44.
Lal, R., J.D.C. Little and J.M. Villas-Boas (1996), ‘A theory of forward buying, merchandising, and trade deals’, Marketing Science, 15 (1), 21–37.
Lal, R. and C. Narasimhan (1996), ‘The inverse relationship between manufacturer and retailer margins: a theory’, Marketing Science, 15 (2), 132–51.
Lal, R. and J.M. Villas-Boas (1998), ‘Price promotions and trade deals with multiproduct retailers’, Management Science, 44 (7), 935–49.
McAlister, L. (2005), ‘Cross-brand pass-through? Not in grocery retailing’, Working Paper, MSI Reports, 05-003.
Messinger, P.R. and C. Narasimhan (1995), ‘Has power shifted in the grocery channel?’, Marketing Science, 14 (2), 189–221.
Meza, S. and K. Sudhir (2006), ‘Pass-through timing’, Quantitative Marketing and Economics, 4 (4), December, 351–82.
Moorthy, S. (2005), ‘A general theory of pass-through in channels with category management and retail com- petition’, Marketing Science, 24 (1), 110–22.
Murry, J.P. and J.B. Heide (1998), ‘Managing promotion program participation within manufacturer–retailer relationships’, Journal of Marketing, 62 (1), 58–68.
Narasimhan, C. (1989), ‘Managerial perspectives on trade and consumer promotions’, Marketing Letters, 1 (3), 239–51.
Narasimhan, C. (1988), ‘Competitive promotional strategies’, Journal of Business, 61 (4), 427–49.
Narasimhan, C. and R.T. Wilcox (1998), ‘Private labels and the channel relationship: a cross-category analysis’, Journal of Business, 71 (4), 573–601.
Neslin, S.A., S.G. Powell and L.S. Stone (1995), ‘The effects of retailer and consumer response on optimal manufacturer advertising and trade promotions strategies’, Management Science, 41 (5), 749–66.
Peltzman, S. (2000), ‘Prices rise faster than they fall’, Journal of Political Economy, 108 (3), 466–502.
Tyagi, R.K. (1999), ‘A characterization of retailer response to manufacturer trade deals’, Journal of Marketing Research, 36 (4), 510–16.
Van Heerde, H.J., S. Gupta and D.R. Wittink (2003), ‘Is 75% of the sales promotion bump due to brand switch- ing? No, only 33% is’, Journal of Marketing Research, 40, 481–91.
Walters, R.J. (1989), ‘An empirical investigation into retailer response to manufacturer trade promotions’, Journal of Retailing, 65 (2), 253–72.
